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import json
import os
import argparse
from tqdm import tqdm
import tiktoken
from openai import OpenAI
from huggingface_hub import hf_hub_download
def gpt_4o(input_text):
client=OpenAI(api_key=os.environ.get("OAI"))
response = client.chat.completions.create(
model="gpt-4o",
messages=[
{"role": "user", "content": [{"type": "text", "text": input_text}]}
],
response_format={"type": "json_object"},
temperature=0,
max_tokens=4096,
top_p=0,
frequency_penalty=0,
presence_penalty=0
)
return response.choices[0].message.content
def run_gpt4_event_extraction(data_dir, max_tokens=100000):
all_info_path = os.path.join(data_dir, "all_info_with_txt.json")
output_dir = os.path.join(data_dir, "gpt4_event_extraction")
os.makedirs(output_dir, exist_ok=True)
icl_path = hf_hub_download(
repo_id="PledgeTracker/demo_feedback",
filename="icl.txt",
repo_type="dataset",
token=os.environ["HF_TOKEN"]
)
ICL = open(icl_path, "r").read()
all_info = open(all_info_path, "r").readlines()
enc = tiktoken.encoding_for_model("gpt-4o")
for i, line in enumerate(all_info):
ID = i
urls = []
results = []
data = json.loads(line)
docs = data["evidence"]
claim = data["claim"]
output_path = os.path.join(output_dir, f"gpt4o_results_{ID}_claim.json")
if os.path.exists(output_path):
print(f"Already exist: {output_path}")
else:
for doc in tqdm(docs):
if doc["url"] in urls:
continue
text = " ".join(doc["text"])
input_text = (
f"{ICL}\nNow please only summarize events that are useful for verifying the pledge '{claim}', and their dates in the JSON format.\n\nInput:\n\nTitle: {doc['metadata']['title']}\n"
f"Date: {doc['metadata']['date']}\nArticle: {text}\nPledge: {claim}\n\n"
f"Output:\n"
)
urls.append(doc["url"])
text_tokens = enc.encode(input_text)
if len(text_tokens) > max_tokens:
input_text = enc.decode(text_tokens[:max_tokens])
try:
output = gpt_4o(input_text)
# print(f"GPT-4o Response: {output}")
results.append({
"url": doc["url"],
"title": doc["metadata"]["title"],
"date": doc["metadata"]["date"],
"article": text,
"output": json.loads(output)
})
except Exception as e:
print(f"Error processing doc: {e}")
continue
with open(output_path, "w", encoding="utf-8") as f:
json.dump(results, f, ensure_ascii=False, indent=4)
return output_path
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Run GPT-4o event extraction")
parser.add_argument("--data_dir", type=str, required=True, help="Root data directory")
parser.add_argument("--icl_path", type=str, required=True, help="Path to ICL prompt file")
parser.add_argument("--max_tokens", type=int, default=100000, help="Maximum token limit for input")
args = parser.parse_args()
run_gpt4_event_extraction(
base_dir=args.base_dir,
icl_path=args.icl_path,
max_tokens=args.max_tokens
)
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